Conventional orthogonal signal-generation methods for single-phase grid suffer from long response time, approximation errors, and/or noise amplification. To remedy this problem, a novel orthogonal signal-generation algorithm, which is characterized by remarkable response speed, high accuracy, noise immunity, and easy implementation, is developed in this paper. The developed algorithm can precisely calculate the orthogonal signal within about 2.5 ms when the amplitude/phase of the grid signal changes suddenly, under the premise of not significantly increasing the computational burden compared with the conventional methods. Far more important is that the high accuracy of the proposed method is independent of the system sampling frequency; hence, effectively avoiding the approximation errors in a wide range of sampling frequencies. In addition, it is shown how the noise amplification issue caused by the developed algorithm, which is nearly equal to that of the first-order differentiating method, can be effectively solved by proper time-span scaling and restricted into an acceptable range. Finally, the validity and advancement of the developed algorithm are verified by experimental results.
A Fast Orthogonal Signal-Generation Algorithm Characterized by Noise Immunity and High Accuracy for Single-Phase Grid
Liu, X;
2016-01-01
Abstract
Conventional orthogonal signal-generation methods for single-phase grid suffer from long response time, approximation errors, and/or noise amplification. To remedy this problem, a novel orthogonal signal-generation algorithm, which is characterized by remarkable response speed, high accuracy, noise immunity, and easy implementation, is developed in this paper. The developed algorithm can precisely calculate the orthogonal signal within about 2.5 ms when the amplitude/phase of the grid signal changes suddenly, under the premise of not significantly increasing the computational burden compared with the conventional methods. Far more important is that the high accuracy of the proposed method is independent of the system sampling frequency; hence, effectively avoiding the approximation errors in a wide range of sampling frequencies. In addition, it is shown how the noise amplification issue caused by the developed algorithm, which is nearly equal to that of the first-order differentiating method, can be effectively solved by proper time-span scaling and restricted into an acceptable range. Finally, the validity and advancement of the developed algorithm are verified by experimental results.File | Dimensione | Formato | |
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